Source: CORNELL UNIVERSITY submitted to NRP
IT'S ABOUT TIME: MULTI-HOST PARASITE SPILLOVER IN TEMPORALLY DYNAMIC COMMUNITIES
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
ACTIVE
Funding Source
AFRI COMPETITIVE GRANT
Reporting Frequency
Annual
Accession No.
1026820
Grant No.
2021-67015-35235
Cumulative Award Amt.
$2,500,000.00
Proposal No.
2021-06296
Multistate No.
(N/A)
Project Start Date
Sep 1, 2021
Project End Date
Aug 31, 2026
Grant Year
2021
Program Code
[A1222]- Ecology and Evolution of Infectious Diseases
Recipient Organization
CORNELL UNIVERSITY
(N/A)
ITHACA,NY 14853
Performing Department
Entomology
Non Technical Summary
Pollinators serve a critical role in our native ecosystems as well as agricultural crops, providing billions of dollars in pollination services annually. Recently, parasites have been linked to declines of several pollinator species, with spillover of parasites from one species to another identified as a major concern. Thus, a better understanding of parasite spillover among bees has important conservation and economic implications. Our project seeks to understand and ultimately control disease spillover in bee communities. We will collect detailed time-varying empirical contact pattern data from plant-pollinator networks and quantify transmission parameters for disease spread at flowers and within colonies of social bees to identify potential transient reservoir communities and/or species. These data will be used to parameterize dynamic models and conduct time-dependent sensitivity analyses of disease spread and spillover. Model predictions will then be tested via whole-community manipulations of bees, parasites and plants in mesocosms. The work outlined in this proposal will provide tangible insight into factors shaping disease spillover in bee communities, which has the potential to improve management efforts, such as guidelines for beekeepers and commercial bee distributers, and the design of pollinator-friendly wildflower strips on state and federal lands.
Animal Health Component
20%
Research Effort Categories
Basic
80%
Applied
20%
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
31138991170100%
Knowledge Area
311 - Animal Diseases;

Subject Of Investigation
3899 - Other animals, general;

Field Of Science
1170 - Epidemiology;
Goals / Objectives
Pollinators serve a critical role in our native ecosystems as well as agricultural crops, providing billions of dollars in pollination services annually. Recently, parasites have been linked to declines of several pollinator species. Thus, a better understanding of parasite spillover among bees has important conservation and economic implications. There is growing recognition that risk of disease spillover in multi-host communities varies in time. The approach in this proposal exploits and further develops a temporally dynamic study system and modeling approach to understanding context-dependent spillover. We will collect detailed time-varying empirical contact pattern data from plant-pollinator networks (Obj. 1) and quantify transmission parameters for disease spread at flowers and within colonies of social bees (Obj. 2) to identify potential transient reservoir communities and/or species. These data will be used to parameterize dynamic models and conduct time-dependent sensitivity analyses of disease spread and spillover. Model predictions will then be tested via whole-community manipulations of bees, parasites and plants in mesocosms (Obj. 3). The work outlined in this proposal will provide tangible insight into factors shaping spillover, which has the potential to inform management efforts, such as guidelines for beekeepers and commercial bee distributers, and the design of pollinator-friendly wildflower strips on state and federal lands.
Project Methods
Objective 1.Identify the pattern of transient reservoir communities and/or species in time-varying networks. Our recent studies have highlighted that community interactions and individual behaviors have non-intuitive effects on disease transmission, due to a complex interplay of factors and effects. In some cases, for example, we cannot be certain a priori whether infection will dilute or amplify within a subnetwork, or identify what subnetworks might become "disease hotspots" that act as a source of infection for other species. Therefore, our first goal is to identify reservoir communities and/or species in the network and their variation throughout the year. To identify the pattern of transient reservoir communities and/or species in time-varying networks with greater precision, we will conduct thorough sampling of bee and flower communities, explicitly considering C. bombi strains within bees and on flowers. We will collect observational data from three plant-pollinator networks in upstate NY old-fields (500 m sampling radius each) by visiting each site 24 times between April-Sept (i.e., once a week), recording the identity and abundance of visitors at flowers of each plant species using a standard transect sampling approach. The data collected under Obj. 1 on floral visitation rates by bee species, and on the temporal population and disease prevalence dynamics at our study sites, will be used to infer seasonal dynamics of transmission parameters in our general model. We will identify key change points in the dynamics and estimate seasonal transmission networks, enabling us to identify seasonal changes in disease reservoirs and probe the dynamics of spillover. Adaptive, targeted screening of bees and flowers for parasites will be carried out to improve estimates of parameters whose uncertainty has the largest impacts on model outputs.Objective 2.Determine which processes promote (or limit) disease spillover from reservoir communities and/or species to species of conservation concern. Our preliminary data and theory/models suggest community context and continuous variation in transmission potential are important determinants of spillover. Thus, we will extend our model to incorporate the quantitative amounts of parasites on flowers and carried by hosts. We will also extend our models to include within-colony transmission among social species. We will also explore how within-colony transmission in social species might alter our previous conclusions. By allowing transmission between individuals specialized on different flower species, within-colony transmission might either ameliorate or enhance the effects of individual specialization.Objective 3.Test experimentally whether optimal control models and time-dependent sensitivity analyses accurately predict impacts on disease spillover and spread in the community. Optimal control offers the opportunity to "turn the knobs" and assess which attributes of a system are most important for predicting the formation of reservoir communities and/or species and subsequent spillover, ultimately informing where and when control measures will be most effective. In our tractable bee-flower system, we can test predictions of these models via whole-community manipulations. This will be an iterative process, with model refinement based on whole-community manipulation results.

Progress 09/01/22 to 08/31/23

Outputs
Target Audience:Target audiences have been reached via peer-reviewed publications, extension publications, and talks to beekeepers, veterinarians, and researchers. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?During the current reporting period, one research associate, one postdoc, one graduate student, and three undergraduates were supported by the project. One postdoc and two graduate students presented data from the project at the American Beekeeping Federation meeting for beekeepers, and the Entomological Society of America meeting, which is primarily attended by scientists. In addition, one summer REU student worked on the project and was afforded opportunities for professional development via writing workshops, statistical analysis workshops, presentations from scientists, and development of their own presentation summarizing their work. How have the results been disseminated to communities of interest?Results have been disseminated via peer-reviewed publications, extension publications, workshops for beekeepers and veterinarians, and talks given to beekeepers, veterinarians, and researchers. What do you plan to do during the next reporting period to accomplish the goals?During the next reporting period we will begin screening bees for pathogens relevant to Obj 1, continue to develop models relevant to Obj 2, and we will begin manipulating communities of bees and flowers as pertinent to Obj 3.

Impacts
What was accomplished under these goals? During the current reporting period we published two peer-reviewed papers, two extension guides for beekeepers and coffee farmers on how to reduce risk of disease spillover near apiaries and agroecosystems, and multiple fact sheets for beekeepers on how to reduce disease in their operations. In addition, we conducted year two of our season-long sampling of pollinator communities to assess Crithidia bombi, Deformed Wing Virus (DWV), and Black Queen Cell Virus (BQCV) prevalence in the bee community (Obj 1), and continued to develop new models for time-dependent sensitivity analyses of disease spread and spillover: one published model and one follow-up model in preparation (Obj 2).

Publications

  • Type: Journal Articles Status: Published Year Published: 2022 Citation: Ng, W. H., S. H. McArt, C. R. Myers and S. P. Ellner. 2022. Pathogen transport amplifies or dilutes disease transmission depending on the host dose-response relationship. Ecology Letters 25:453-465. https://doi.org/10.1111/ele.13932
  • Type: Journal Articles Status: Published Year Published: 2023 Citation: Ng, W. H., C. R. Myers, S. H. McArt and S. P. Ellner. 2023. Predicting and controlling spillover in multi-species disease transmission networks: Steady-state analysis. The American Naturalist 201:880-894. https://doi.org/10.1086/724009
  • Type: Other Status: Published Year Published: 2023 Citation: Hinsley, C. A., C. Crosier, B. DeMoras, J. Mahoney, K. R. Deutsch and S. H. McArt. 2023. New York State Beekeeper Tech Team Report: 2022 Annual Summary. Cornell University. 32 pp. https://cornell.app.box.com/v/2022-tech-team-annual-report
  • Type: Other Status: Published Year Published: 2023 Citation: Lindsay, S. E., C. L. Davis, D. E. Sossa, V. Ruiz-Gutierrez and S. H. McArt. 2023. Assessing the potential benefits and biodiversity impacts of non-native honey bees in coffee systems. Report for Nespresso, Inc. 25 pp. https://blogs.cornell.edu/mcartlab/files/2024/07/Non-native-honey-bees-in-coffee-systems_Cornell_September2023.pdf


Progress 09/01/21 to 08/31/22

Outputs
Target Audience:Target audiences have been reached via peer-reviewed publications, extension publications, and talks to beekeepers, veterinarians, and researchers. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?During the current reporting period, one graduate student was supported by the project. Two graduate students, one postdoc, and one research associate presented data from the project at the Eastern Apiculture Society meeting for beekeepers, and the Entomological Society of America meeting, which is primarily attended by scientists. In addition, three summer REU students worked on the project and were afforded opportunities for professional development via writing workshops, statistical analysis workshops, presentations from scientists, and development of their own presentations summarizing their work. How have the results been disseminated to communities of interest?Results have been disseminated via peer-reviewed publications, extension publications, workshops for beekeepers and veterinarians, and talks given to beekeepers, veterinarians, and researchers. What do you plan to do during the next reporting period to accomplish the goals?During the next reporting period we will continue to collect observational data relevant to Obj 1, develop models relevant to Obj 2, and we will begin manipulating communities of bees and flowers as pertinent to Obj 3.

Impacts
What was accomplished under these goals? During the current reporting period we published four peer-reviewed papers, one extension guide for beekeepers on how to reduce disease in their operations, and conducted three trainings for veterinarians on honey bee biology, health, and disease control. In addition, we conducted a season-long field experiment to assess Crithidia bombi prevalence in the bee community (Obj 1) and started developing new models and conducting time-dependent sensitivity analyses of disease spread and spillover (Obj 2).

Publications

  • Type: Journal Articles Status: Published Year Published: 2021 Citation: Figueroa, L. L., C. Grincavitch and S. H. McArt. 2021. Crithidia bombi can infect two solitary bee species while host survivorship depends on diet. Parasitology 148:435-442. https://doi.org/10.1017/S0031182020002218
  • Type: Journal Articles Status: Published Year Published: 2021 Citation: Adler, L. S., R.E. Irwin, S. H. McArt and R. L. Vannette. 2021. Floral traits affecting the transmission of beneficial and pathogenic pollinator-associated microbes. Current Opinion in Insect Science 44:1-7. https://doi.org/10.1016/j.cois.2020.08.006
  • Type: Journal Articles Status: Published Year Published: 2021 Citation: Figueroa, L. L., S. M. Compton, H. Grab and S. H. McArt. 2021. Functional traits linked to pathogen prevalence in wild bee communities. Scientific Reports 11:7529. https://doi.org/10.1038/s41598-021-87103-3
  • Type: Journal Articles Status: Published Year Published: 2021 Citation: Davis, A. E., K. R. Deutsch, A. T. Gonzales, M. J. Mata Loya, L. V. Cody, E. Harte, P. A. Mu�iz, W. H. Ng and S. H. McArt. 2021. Eristalis flower flies can be mechanical vectors of the common trypanosome bee parasite, Crithidia bombi. Scientific Reports 11:15852. https://doi.org/10.1038/s41598-021-95323-w
  • Type: Other Status: Published Year Published: 2022 Citation: Hinsley, C. A., B. DeMoras, C. Crosier and S. H. McArt. 2022. 2022 New York State Beekeeper Tech Team Spring Colony Health Report. 6 pp. https://cornell.app.box.com/v/2022-tech-team-spring-report